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The Markov Property, Chain, Reward Process and Decision Process

The Markov Property, Chain, Reward Process and Decision Process

As seen in the previous article, we now know the general concept of Reinforcement Learning. But how do we actually get towards solving our third challenge: "Temporal Credit Assignment"? To solve this, we first need to introduce a generalization of our reinforcement models. When we look at these

Ordinary Least Squares (OLS)

Ordinary Least Squares (OLS)

Let's start by defining the goal of our algorithm, what do we want to achieve with our OLS algorithm? Well if we have data points in a region (or XY-axis), then we want to be able to find an equation that fits as closely to these points as

Getting AMQP to work in your browser

Getting AMQP to work in your browser

For one of my customers, I had to be able to connect to an EventHub through the browser, so how did I do this? So we know that EventHub works with the AMQP protocol, so what if we could get this working in the frontend? After fiddling a bit with

Installing OpenAI Gym in a Windows Environment

Installing OpenAI Gym in a Windows Environment

Reinforcement learning does not only requires a lot of knowledge about the subject to get started, it also requires a lot of tools to help you test your ideas. Since this process is quite lengthy and hard, OpenAI helped us with this. By creating something called the OpenAI Gym, they

Multi-armed bandit framework

Multi-armed bandit framework

To start solving the problem of exploration, we are going to introduce the Multi-armed bandits framework. But what exactly does this solve? Just think that you are executing a clinical trial with 4 pills. You know that the pills have a survival rate but you don't know what

Connect to your Docker Daemon through the Windows Subsystem for Linux (WSL)

Connect to your Docker Daemon through the Windows Subsystem for Linux (WSL)

Do you have Windows installed and you love using the Linux Subsystem on it? (commonly known as WSL) Well let me tell you the steps to achieve this. Let's start by Install the docker client on your WSL, which you can do this easily through this command: # Install

An introduction to Reinforcement Learning (RL)

An introduction to Reinforcement Learning (RL)

So as we learned in the intro to Machine Learning, Reinforcement Learning is this technique where we have an agent who will take specific actions on an environment to try to reach an optimal state. But how can we illustrate this? Take a look at the following picture. We can